Image-based jam detection

ABSTRACT

Apparatus and associated methods relate to a method of non-contact motion detection. A one-dimensional optical sensor detects motion of a target or objects on a conveyor belt through a continuous measurement of targets or objects and a real-time comparison of the pixel images captured by the one-dimensional optical sensor. In an illustrative embodiment, a one-dimensional sensor may be configured to determine motion of objects based on changes to the captured intensities of pixel images over time. The sensor may continually capture photoelectric pixel images and compare a current pixel image with a previous pixel image to determine a frame differential image value. The frame differential image value is evaluated against a predetermined threshold over a predetermined time period. Based on the evaluation, a signal is output indicating whether the objects on the conveyor belt are moving or jammed.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional Application Ser.No. 62/916,087 titled “IMAGING SYSTEM USING TRIANGULATION,” filed byBanner Engineering Corp. on Oct. 16, 2019. This application also claimsthe benefit of U.S. Provisional Application Ser. No. 62/924,020 titled“IMAGING SYSTEM USING TRIANGULATION,” filed by Banner Engineering Corp.on Oct. 21, 2019.

This application incorporates the entire contents of the foregoingapplication(s) herein by reference.

TECHNICAL FIELD

Various embodiments relate generally to non-contact motion detection andmore specifically to a system and method of motion detection forconveyors.

BACKGROUND

Conveyor belts typically transport objects from a first location to asecond desired location. Many different types of conveyor belts exist.For example, conveyor belts may consist of surfaces that includerollers, wheels, belts that may be webbed or textured, or some othersurface that would easily enable the movement of materials or objectsfrom one place to another. The objects being transported may be varied.For example, objects may be non-uniform, such as individual boxes ofvarying sizes and shapes, or continuous and uniform, such as a long rollof paper or paper towels.

Conveyor belt applications typically monitor the progress of objects ona conveyor belt. Specifically, conveyor belt applications may need todetermine whether a flow of objects along the conveyor belt are movingfreely or if the objects are stopped and no longer moving or jammed. Insome cases, the determination of flow of objects on the conveyor beltinvolves direct human intervention by a user. For example, the user maydirectly observe the objects as they move along the belt from one pointto another. In other cases, the monitoring of object flow may be done bya camera-based system that records the movement of the objects as theyare transported along the conveyor belt.

It may be especially challenging to determine whether or not objects ona conveyor belt are moving or are jammed in cases where objects on theconveyor belt are continuous or uniform rather than discrete andnon-uniform in size and/or shape. For example, it may be more difficultto detect whether a long roll of paper or paper towels are continuing tomove along a conveyor belt or are stopped as opposed to individual boxesof varying sizes and shapes.

SUMMARY

Apparatus and associated methods relate to a method of non-contactmotion detection. A one-dimensional optical sensor detects motion of atarget or objects on a conveyor belt through a continuous measurement oftargets or objects and a real-time comparison of the pixel imagescaptured by the one-dimensional optical sensor. In an illustrativeembodiment, a one-dimensional sensor may be configured to determinemotion of objects based on changes to intensities of the captured pixelimages over time. The sensor may continually capture photoelectric pixelimages and compare a current pixel image with a previous pixel image todetermine a frame differential image value. The frame differential imagevalue is evaluated against a predetermined threshold over apredetermined time period. Based on the evaluation, a signal is outputindicating whether the objects on the conveyor belt are moving orjammed.

Various embodiments may achieve one or more advantages. For example, inone exemplary aspect, a cost-competitive and economical advantageresults from using a minimal amount of hardware for jam detection. Forexample, a single optical imaging source, such as a one-dimensionalsensor, may launch a linear optical beam that illuminates a targetobject being transported by a conveyor system and generate a detectionsignal as a function of a reflection of the linear optical beam off thetarget object and incident on a corresponding detection surface. Thedetection signal may indicate whether the object is jammed or moving.The only hardware required for achieving detection results is theoptical imaging source which may include both a laser and linear imagerfor a measurement of distance and pixel intensity and the processingengine. In some embodiments, steps of a method may advantageouslyprovide for image processing to determine motion based on sensormeasurements of a frame differential image (FDI) without regard todistance.

In some embodiments, a FDI value may indicate a measure of movement ofthe target object from the first detection time to the second detectiontime. Some embodiments may generate a jam detection signal only if areceived pixel signal strength and/or distance measurement is within apredetermined qualified range. This may reduce, for example, falsedetections of jams.

In another exemplary aspect, a further advantage may be the easydetection of movement of uniform and/or light-colored objects,dark-colored objects or even multi-colored objects on a conveyer belt.This may be accomplished by a processor programmed with instructions tooperate an algorithm that compares differences in pixel signal strength.For example, the algorithm may include operations that sum the square ofthe differences in pixel strength to produce a residual difference thatmay indicate a motion or jam state over a predetermined time period.

The details of various embodiments are set forth in the accompanyingdrawings and the description below. Other features and advantages willbe apparent from the following detailed description taken in conjunctionwith the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

For a more complete understanding of the disclosure and the advantagesthereof, reference is now made to the accompanying drawings whereinsimilar or identical reference numerals represent similar or identicalitems.

FIG. 1 depicts a view of an exemplary implementation of a system formotion detection;

FIG. 2 depicts a top-level block diagram of an exemplary jam detectionengine;

FIGS. 3A-3E depict graphs of exemplary light intensity for each pixelimage captured by the sensor of FIG. 1 to illustrate the processingsteps for jam detection;

FIG. 4A depicts a graphical output of an exemplary amount of changecalculated between pixel image signals;

FIG. 4B depicts a graphical display of an exemplary amount of change fora moving object as compared to a predetermined threshold;

FIG. 5 depicts a graphical display of an exemplary jam detectionprocess;

FIG. 6 depicts a flowchart detailing an exemplary process of motiondetection; and

FIG. 7 depicts a block diagram of an exemplary system environment.

DETAILED DESCRIPTION OF ILLUSTRATIVE EMBODIMENTS

To aid understanding, this document is organized as follows. First, anexemplary use case of a scanner deployed to detect motion of a conveyorbelt is briefly introduced with reference to FIG. 1 . Next, withreference to FIG. 2 , a discussion of a top-level operation of jamdetection engine with the scanner is presented. With reference to FIGS.3A-3E, the discussion details the method of image processing thatdetermines motion based on sensor measurements of a frame differentialimage (FDI). Turning to FIGS. 4A and 4B, the graphical output of theamount of change detected between pixel images and its relevance tomotion detection is discussed. A discussion of the motion detectoroutputs that indicates whether or not a jam exists is presented withrespect to FIG. 5 . With reference to FIG. 6 , the process of motiondetection according to embodiments of the disclosure is discussed.Finally, a review of an exemplary system that may implement the processof j am detection is presented with reference to FIG. 7 .

In embodiments of this disclosure, an optical imaging source, such as asensor device having a plurality of photoelectric receiving elements orpixels, scans target objects moving on a conveyor belt and creates aone-dimensional array. The one-dimensional pixel array is processed by amonitor system and determines one or more FDI values of the pixel imagesto determine whether the target objects are moving on the conveyor beltor the target objects are jammed.

In various embodiments, the sensor may include a laser and aone-dimensional linear imager. The signal strength of each pixel imageacross the one-dimensional linear imager scan may be measured. Thesensor may then process the difference between the pixel signalstrengths over time to determine whether an object is movingcontinuously on a conveyor belt. In some embodiments, a distance may bemeasured through the laser by optical triangulation which determinesobject position by measuring light reflected from the target object. Thesensor may then process the difference between the pixel signalstrengths and/or distances over time to determine whether an object ismoving continuously on a conveyor belt.

FIG. 1 depicts a view of an exemplary implementation of a system formotion detection. In this embodiment, an optical imaging source orsensor 110 is illustrated as operating on objects, such as object 130,moving along a conveyor belt 124 of a conveyor 120. The sensor 110 mayinclude a laser 112 and a linear imager 114. The linear imager 114 maybe one-dimensional and include a single line of photoelectric receivingelements (PERE) or pixels. Photoelectric receiving elements may beassociated with corresponding pixels. By way of example, and notlimitation, the number of individual photoelectric receiving elements orpixels in linear imager 114 may number around 640.

The conveyor 120 may consist of a frame 122 that supports the conveyorbelt 124. The conveyor 120 may vary in width to accommodate targetobjects of varying sizes that may pass singularly, in tandem, orside-by-side along the conveyor belt 124 in front of the sensor 110.

In operation, the sensor 110 is parallel to the conveyor 120 and mayproject a beam of light 116 along the conveyor belt 124. The beam oflight 116 may be a diffuse light that is generated from a light emittingdevice such as laser 112. The beam of light 116 is directed onto targetobjects, such as object 130, as they move along the conveyor belt 124and pass in front of sensor 110. The beam of light 116 reflects off theconveyor belt objects and the reflected light 144 forms aone-dimensional array of signals on the pixels or PERE of the linearimager 114. Each signal of the one-dimensional signal array has anintensity or strength that may be measured by the linear imager 114.

The sensor 110 may be a triangulation sensor configured by amicrocontroller or processor to detect conveyor belt motion. In anillustrative embodiment, a processor within the sensor 110 may control amonitor system 152 configured to determine whether objects on a conveyorbelt are moving or jammed. In this disclosure, the illustration of themonitor system 152 is not meant to imply physical or architecturallimitations. Different implementations may be possible as may be obviousto one skilled in the art. The monitor system 152 may include a jamdetection engine 154. Jam detection engine 154 may output one or moresignals that indicate the state of the conveyor belt 124 as moving orjammed. The signals may be sent to one or more machines 160 that mayactivate a response based on the output state received from the jamdetection engine 154. In some embodiments, the output of the jamdetection engine 154 may be sent to controlled machines 160 for furtheraction. For example, the output of the jam detection engine 154 may besent to alert a user to manually intervene and clear the jam state. Inother embodiments, the output of the jam detection engine 154 may beused to operate some other device, including, but not limited to, aplunger, to remove the cause of the jam state.

FIG. 2 depicts a top-level block diagram of an exemplary jam detectionengine. In FIG. 2 , the jam detection engine 210 may input imagedifference signals 212. The image difference signals 212 are determinedby a detection signal analysis that compares an amount of changedetected for an image at two discrete time intervals. The jam detectionengine 210 may also input threshold 214. The threshold 214 may functionas a user-defined sensitivity setting. Jam detection engine 210 maycompare the image difference signals 212 to the threshold 214 setting todetermine whether a conveyor belt is in a moving or jammed state. Basedon the determination, the jam detection engine 210 may output a jam 220or motion 222 signal.

The threshold 214 is a sensitivity setting parameter that may beadjusted. In some embodiments, the adjustment of threshold 214 may bedone by a user input control, for example and without limitation, anadjustment knob, on the jam detection engine that may be dialed upwardor downward. The threshold 214 may be adjusted based on userrequirements or sensitivity requirements. For example, the threshold maybe lowered if greater sensitivity is needed to be able to detect amotion state. Alternatively, the threshold may be increased for lesssensitivity to decrease the possibility non-detection of a jam state.For example, in a scenario where a conveyor belt may experiencesignificant amounts of vibration that causes the objects on the conveyorbelt to be moved around a lot during a jam, a user may set the thresholdto a high setting to prevent a non-detection of a jam state.

FIGS. 3A-3E depict graphs of exemplary light intensity for each pixelimage captured by the sensor 110 of FIG. 1 to illustrate the processingsteps for jam detection. In the graphs of FIGS. 3A-3E, the X-axes mayrepresent a pixel number in a one-dimensional array of PERE or pixels ofa sensor. The Y-axes may represent an amplitude or magnitude of theactual signal corresponding to the individual pixel. The amplitude orvalue of the signal shown on the Y-axis may be a measure of the signalintensity. The signal value is based on light reflected back to animager of a sensor, such as imager 114 of sensor 110 illustrated in FIG.1 .

In the embodiment of FIG. 3A, it may be observed from the X-axis thatthe linear pixel array numbers about twenty pixels. However, only aboutseven pixels, starting at about pixel eight through about pixel thirteenhave a signal value that indicates a light or signal intensity. Theamplitude of the signal is a measure of the signal intensity. The signalvalue is based on light reflected back off of an object onto the imager.

It must be understood that the depicted graphs, starting at FIG. 3A, donot take into account background light that may not be a direct resultof reflected light coming directly back into the imager, such as ambientor scattered light. In embodiments of this disclosure, ambient orscattered light is automatically excluded from consideration by thesensor. The light exclusion may be performed by the sensor prior to alaser or other optical imaging source launching or emitting an opticalbeam. The sensor may take a sample or snapshot of light received on theone-dimensional array prior to the firing of the laser. The pixel valuesof the received light are then subtracted out from the pixel values ofthe reflected light after the emission of the optical beam. As a result,the pixels of the array that do not directly receive any reflected lightmay have a value of around zero.

FIG. 3B illustrates a general profile of an object formed by pixelimages resulting from light reflected off the imager by the object. InFIG. 3B, the signal values of each pixel are normalized so that thevalue of any pixel that does not receive light is set to zero andignores ambient light. The profile generated by the object may depend onthe optical system which receives the light that is reflected. In someembodiments, the reflected light may result in a profile that may begenerally bell-shaped or Gaussian. In other embodiments, the profilegenerated may depend on the surface of the object or target. Forexample, a diffuse target provides a smooth response.

The pixel values may be normalized based on the setting used by thesensor to capture the image. The exposure rate used by the sensorautomatically changes depending on the distance of the sensor from theobject and the color of the object as a normal part of the triangulationalgorithm of the sensor. In embodiments that feature atriangulation-based sensor, the amplitude of the signal may beautomatically adjusted with respect to dark or light objects forpurposes of more accurately determining distance.

For example, if two dark targets are far from the imager, the sensorexposure rate may need to be increased in order for the sensor todetermine the presence of the target. Alternatively, if two whitetargets are really close to the imager, then the sensor exposure ratemay need to be decreased or turned down. If only one exposure rateexisted for the sensor, it may be difficult to recognize dark targets ata distance. Some embodiments may undo the output of the triangulationalgorithm, for example, and normalize the amplitude based on the settingused by the sensor that may be set by a user.

Turning now to FIG. 3C, a graph 320 illustrates a comparison of aprevious image in time with a current image on a pixel-by-pixel basis.In FIG. 3C, the comparison shows amplitude differences between twoimages or objects. As illustrated in the graph 320 of FIG. 3C, at 322,pixel 8 at a first point in time of the current image is brighter thanpixel 8 of the current image at a second point in time. Therefore, thecurrent image has a larger amplitude or signal value. At 324, pixel 9 ofthe current image at a first point in time is darker than pixel 9 of thecurrent image at a second point in time. Therefore, the current image ata second point in time has a smaller value. A difference in distancebetween the current image at a first point in time and the current imageat a second point in time would be illustrated by a difference inalignment between the pixels. The jam detection engine is responsive toany change between pixels and processes amplitude differences ordistance differences in the same way.

Turning now to FIG. 3D, the process calculates a residual difference, inmagnitude on a pixel-by-pixel basis, of the pixel image at a first timeperiod from the pixel image at a second time period. In the graph 340 ofFIG. 3D, for example, the residual differences illustrated at 342, 344,346, 348 and 350 correspond, respectively, to the differences betweenthe pixels illustrated in the graph 320 of FIG. 3C at 322, 324, 326,328, and 330.

In varying embodiments, the varying amplitude of the pixels may providean indicator of a motion state. For example, in the graph 340 of FIG.3D, pixels that have a signal value as indicated by the Y axis may becharacterized as an object in motion since the amplitude of the pixelsare varying. Alternatively, a continuous amplitude of around zero mayindicate that a jam state exists.

The process continues with squaring each residual difference calculatedin FIG. 3D to produce a positive real number for each pixel thatrepresents the amplitude of the pixel. The square of the differenceaccentuates or increases the contrast or difference between two images.The amplitude of each of the pixels in the image are then summedtogether to produce a single amplitude or a single dimensional variable.The process may then use some other normalization function to normalizethe noise produced by an object close to the sensor versus an object atsome distance away from the sensor. For example, the sum of the squareof the differences may be normalized by dividing out the number ofactive pixels.

Referring now to FIG. 3E, the graph 360 illustrates the magnitudesquared of each of the pixels at two different times. Some of themagnitudes of each pixel shown in graph 360 represents the signal ofamount of change between the two different times. The pixels in graph360, representing the sum of the square of the differences betweenpixels, correspond to the pixels illustrated in graph 340 of FIG. 3D.For example, pixels 362, 364, 366, 368, and 370 of graph 360 of FIG. 3Ecorrespond, respectively, to pixels 342, 344, 346, 348, and 350 of graph340 of FIG. 3D.

In an illustrative example, FIG. 4A illustrates a graph of the sum ofthe square of the differences, on the Y axis, versus time, on the Xaxis, when a target may be moving. Conversely, FIG. 4B illustrates agraph of the sum of the square of the differences when a target may bemoving.

FIG. 4A represents an amount of change in amplitude in time between acurrent target and a previous target. In FIG. 4A, the graph 400illustrates the calculated amount of change for a target that isstationary. For a stationary target, the change in the signal 420 may berelatively zero, for example, responsive only to substantial measurementnoise, and therefore the signal difference would be small as compared toa pre-determined threshold 440 setting. Each point along the X-axis ofthe graph 400 represents the calculated amount of change that is derivedfrom the sum of squares of the differences with any normalized amplitudecorrection. Each point represents how much the current image isdifferent from the previous image.

FIG. 4B depicts a graphical display of the amount of change as comparedto a predetermined threshold. The threshold 460 is a user-definedsensitivity setting. In FIG. 4B, the graph 450 illustrates thecalculated amount of signal 470 change for a target that is moving pastthe sensor. The motion state is indicated by the amount of signal 470change being consistently above the threshold 460 setting. A jam stateis indicated when the amount of change is consistently below thethreshold 460 setting. The threshold 460 may be adjusted upwards ordownwards depending on the application and the amount of sensitivitythat may be needed to detect a motion state or a jam state. For example,the threshold 460 may need to be adjusted to a high setting in a casewhere there may be a lot of vibration on a conveyor belt and objects onthe conveyor belt may be jostling around in order to avoid non-detectionof a jam state.

The amount of large and sporadic amounts of change illustrated in FIG.4B accounts for object contrasts or differences including, but notlimited to, laser speckling, object wobble, inherent color differencesof an object, object distance from the sensor. The system keeps track ofhow often the change in amplitude is above or below the thresholdsetting. A consistently low amount of change that is below the thresholdindicates a jam state of the conveyor belt. A consistently sporadic orlarge amount of change above the threshold indicates a motion state ofthe conveyor belt.

FIG. 5 depicts a graphical display of an exemplary jam detectionprocess. In FIG. 5 , the signal 540 may represent an actual number ofcounts within a predetermined timeframe. At a point in time, such as at530, the count may fall below a moving threshold 520 to signal apossible jam. However, when the count falls below a jam threshold 560for a predetermined period of time, a jam state may be indicated. Theindicator of a jam state may include, for example, without limitation, avisual or audible alert or similar operator notification. Similarly, forexample, at a point in time 550 when the count signal 540 increasesabove the moving threshold 520, a state of motion may be signaled.

FIG. 6 depicts a flowchart detailing an exemplary process of motiondetection. The process begins at 610 where a plurality of photoelectricreceiving elements or image pixels are captured by the image scan of anobject over a predetermined time period. The image signal may provide anindication of the distance of the target. At 620, for each of theplurality of image pixels, an image signal is generated so that acurrent pixel image value is compared to a predetermined minimum value.A frame differential image value (FDI) is determined based on thecomparisons at 640. At 640, the difference between a current FDI valueand a previous FDI value is determined. At 650, the difference iscompared with a predetermined threshold. If the FDI value is less thanthe predetermined threshold at 650, a Jam sample signal may be output toa demodulation counter state machine and at 660 the motion count isdecremented. If the FDI value is not less than the predeterminedthreshold, then a Motion sample signal is output to a demodulationcounter state machine and at 670, the motion count is incremented.

The demodulation counter state machine keeps count of the number ofmotion signals over a configurable history of time. At 680, if themotion count exceeds a motion threshold, then at 682 the sensor outputsa moving state on a discrete output. At 662, if the motion count fallsbelow the jam threshold, then at 664, the sensor outputs a jam state ona discrete output. In some embodiments, the sensor may not enforce anyspecific action when in a jam or motion state. The sensor may justindicate the existence of a jam state or motion state (e.g., bygenerating and transmitting an alarm signal) for further action.

FIG. 7 depicts a block diagram of a computer system environment 700 thatmay be operable for various embodiments of the disclosure. In anillustrative embodiment, computer system environment 700 includes amonitor system 710. Monitor system 710 may include a jam detectionengine 702 and detection signal processor 722. In some embodiments,detection signal processor 722 may include an A/D converter 712 andimages detector 714. Other modules may be included such as a processor708, a program memory 718, RAM 716, a laser controller 704, a laser 706,and I/O 720. Those skilled in the art will appreciate that computersystem environment 700 is illustrative and not intended to limit thescope of embodiments. Specifically, computer system environment 700 mayinclude fewer or more components than shown in FIG. 7 to perform themethods described.

In particular, the computing system and devices may include anycombination of hardware and/or software that can perform the indicatedfunctions, including computers, application specific integrated circuits(ASICs), field programmable gate arrays (FPGAs), network devices, andinternet applications, including, for example and without limitation,web-based applications. The computer system environment may also beconnected to other devices that are not illustrated, or instead mayoperate as a stand-alone system. In addition, the functionality providedby the illustrated components may in some embodiments be combined withfewer components or distribute in additional components. Similarly, insome embodiments the functionality of some of the illustrated componentsmay not be provided and/or other additional functionality may beavailable.

In some embodiments, the jam detection engine 702 may include a counterwhich keeps track of the number of times over a predetermined timeperiod that the amplitude is greater than the threshold setting. Thepredetermined time period may be programmed or set by a user torepresent a finite period of time over which the count response isevaluated. The evaluation of the count response may be used to determinewhether or not a jam state or a motion state exists. The counter may beincremented each time the amplitude is greater than the thresholdsetting and decremented each time the counter is less than the thresholdsetting.

Those skilled in the art will also appreciate that, while various itemsare illustrated as being stored in memory or a data store, these itemsor portions of them may be transferred between memory and other storagedevices for purposes of memory management and data integrity.Alternatively, in other embodiments, some or all of the softwarecomponents may execute in memory on another device and communicate withthe illustrated computing system via inter-computer communication.

Those skilled in the art will also appreciate that in some embodimentsthe functionality provided by the methods and systems discussed abovemay be provided in alternative ways, such as being split among moresoftware modules or routines or consolidated into fewer modules orroutines. Similarly, in some embodiments, illustrated methods andsystems may provide more or less functionality than is described, suchas when other illustrated methods instead lack or include suchfunctionality respectively, or when the amount of functionality that isprovided is altered. In addition, while various operations may beillustrated as being performed in a particular manner (e.g., in serialor in parallel) and/or in a particular order, those skilled in the artwill appreciate that in other embodiments the operations may beperformed in other orders and in other manners.

Although a number of embodiments have been described with reference tothe Figures, it will be understood that various modifications may bepossible. For example, although the current disclosure describes apredetermined threshold as being a setting that is user-defined, a usermay establish a threshold setting in a learn mode of the monitor systemand forget it. Advantageous results may be achieved if the thresholdsetting is automatically adjusted by the monitor system after theinitial setting to more finely calibrate a threshold setting. In anotheradvantageous modification, the monitor system may be configured to learnthe criteria that identifies a motion state, establish the learnedcriteria as a baseline to detect motion and automatically calibrate athreshold based on the learned criteria. In yet another advantageousembodiment, the monitor system may be configured to enable both auser-defined threshold and a machine learned threshold.

In one exemplary aspect, an apparatus may include an optical imagingsource adapted to launch an optical beam to illuminate a target objectbeing transported by a conveyor system; a spatially distributed two ormore photoelectric receiving elements (PERE), each of the plurality ofPERE arranged to generate a detection signal at least as a function ofan intensity of a reflection of the linear optical beam off of thetarget object and incident on a corresponding detection surface of eachof the plurality of PERE; a detection signal processing moduleoperatively coupled to receive, from each one of the plurality of PERE,the corresponding generated detection signal at each of a plurality oftemporally-spaced detection times, and to generate an image signalindicative of a motion of the target object based on the generateddetection signals; a processor operatively coupled to receive, from thedetection signal processing module, the image signals generated for eachof the plurality of PERE; and, a data store operatively coupled to theprocessor and containing instructions that, when executed by theprocessor, cause the processor to perform operations to detect a jamstate of the target object being transported by the conveyor system. Theoperations may include (a) receive, for each of the two or more PERE,the image signal at a first one of the detection times and the imagesignal at a second one of the detection times; (b) for each of theplurality of PERE, compare the image signal at the first detection timeto the image signal at the second detection time; (c) based on thecomparison, determine a frame differential image (FDI) value indicativeof a measure of movement of the target object from the first detectiontime to the second detection time; and, (d) if the determined FDI valueis less than a predetermined threshold, then generate a jam detectionsignal.

In some embodiments, the operations may further include: (c1) repeatingsteps (a)-(c) at least a predetermined number of times to determine anFDI value as a function of each of the FDI determinations.

In some embodiments, the detection signal processing module may furthergenerate, for each of the plurality of PERE, the image signal bysubtracting an ambient light level associated with background lightincident on the corresponding detection surface.

In some embodiments, comparing the image signal at the first detectiontime to the image signal at the second detection time additionally mayinclude summing the squares of the differences between each of therespective image signals at the first detection time to thecorresponding image signals at the second detection time. In someembodiments, the optical imaging source may further include aone-dimensional laser source.

In some embodiments, the operations may further include receiving, viathe spatially distributed plurality of photoelectric receiving elements(PERE), a distance measurement to the target object. In otherembodiments, the operations additionally include generating the jamdetection signal only if the received distance measurement to the targetobject is within a predetermined qualified range.

In some embodiments, subtracting the ambient light level associated withbackground light incident on the corresponding detection surface mayinclude adjusting the image signal value to zero if the image signal isless than a predetermined minimum signal threshold for each of the imagesignals associated with each of the plurality of the PERE.

In some embodiments, the image signal value may be adjusted to zero ifthe image signal is less than a predetermined minimum signal threshold.

In some embodiments, the operation to determine a frame differentialimage (FDI) value may further comprise normalizing the FDI as a functionof the number of the image signal values that are non-zero.

In some embodiments, each of the generated detection signals may furtherbe a function of an intensity of the corresponding reflection of thelinear optical beam off of the target object. In some embodiments, eachof a plurality of temporally spaced detection times may further includea corresponding time interval during which each of the correspondingdetection signals are generated.

In some embodiments, the spatially distributed plurality ofphotoelectric receiving elements (PERE) may include a linear array ofPERE. In some embodiments, the spatially distributed plurality ofphotoelectric receiving elements (PERE) may further include atwo-dimensional array of PERE.

In some embodiments, the detection signal processing module may furtherinclude an analog-to-digital converter. In some embodiments, thedetection signal processing module and the processor may furthercomprise a microcontroller.

In one exemplary aspect, a monitor system for non-contact motiondetection may include a processor, an optical imaging source comprisinga spatially distributed plurality of photoelectric receiving elements(PERE) and configured by the processor to detect motion, and a datastore operatively coupled to the processor. The data store may containinstructions that, when executed by the processor, cause the processorto perform operations that include comparing, for each of the pluralityof PERE, values of the PERE processed by the optical imaging source to apredetermined minimum value; determining, for each of the PERE, a framedifferential image (FDI) value based on the comparisons; determining anamount of change based on an analysis of a difference between an FDIvalue at a first time and an FDI value at a second time; comparing thedetermined amount of change with a predetermined threshold; andgenerating a signal that indicates a jam state or a motion state basedon the comparison.

In some embodiments, the monitor system may include an applicationspecific integrated circuit (ASIC) including an interface for connectionto the processor. The ASIC may include circuitry for controllingoperations of the processor.

In one exemplary embodiment, a method of non-contact motion detectionmay include the sampling of a target object by an optical imaging sourcethat has a plurality of temporally separated photoelectric receivingelements (PERE); determining, for each of the plurality of PERE, a framedifferential image (FDI) value; comparing corresponding FDI values ofthe temporally separated pixel images; assessing whether or not the FDIvalues are less than a predetermined threshold value; and generating ajam state signal responsive to one or more FDI values being less thanthe predetermined threshold value for a predetermined period of time.

In some embodiments, comparing corresponding frame differential image(FDI) values may include summing the square of a difference between thecurrent FDI value and a previous FDI value.

A number of implementations have been described. Nevertheless, it willbe understood that various modifications may be made. For example,advantageous results may be achieved if the steps of the disclosedtechniques were performed in a different sequence, or if components ofthe disclosed systems were combined in a different manner, or if thecomponents were supplemented with other components. Accordingly, otherimplementations are contemplated.

What is claimed is:
 1. An apparatus comprising: an optical imagingsource adapted to launch a linear optical beam to illuminate a targetobject being transported by a conveyor system; a spatially distributedplurality of photoelectric receiving elements (PERE), each of theplurality of PERE arranged to generate a detection signal at least as afunction of an intensity of a reflection of the linear optical beam offof the target object and incident on a corresponding detection surfaceof each of the plurality of PERE; a detection signal processing moduleoperatively coupled to receive, from each one of the plurality of PERE,the corresponding generated detection signal at each of a plurality oftemporally-spaced detection times, and to generate, based on generateddetection signals, corresponding image signals indicative of a motion ofthe target object; a processor operatively coupled to receive, from thedetection signal processing module, the image signals generated for eachof the plurality of PERE; and, a data store operatively coupled to theprocessor and containing instructions that, when executed by theprocessor, cause the processor to perform operations to detect a jamstate of the target object being transported by the conveyor system,wherein the operations comprise: (a) receive, for each of the pluralityof PERE, a first image signal of the image signals at a first one of thedetection times and a second image signal of the image signals at asecond one of the detection times; (b) for each of the plurality ofPERE, compare the first image signal at the first detection time to theimage signal at the second detection time; (c) based on the comparison,determine a frame differential image (FDI) value indicative of a measureof movement of the target object from the first detection time to thesecond detection time; and, (d) if the determined FDI value is less thana predetermined threshold, then generate a jam detection signal.
 2. Theapparatus of claim 1, the operations further comprising: (c1) repeatingsteps (a)-(c) at least a predetermined number of times to determine anFDI value as a function of each of the FDI determinations.
 3. Theapparatus of claim 1, wherein the detection signal processing modulegenerating the image signal for each of the plurality of PERE comprisessubtracting an ambient light level associated with background lightincident on the corresponding detection surface.
 4. The apparatus ofclaim 3, wherein subtracting the ambient light level associated withbackground light incident on the corresponding detection surfacecomprises adjusting a value of the image signal to zero if the imagesignal is less than a predetermined minimum signal threshold for each ofthe image signals associated with each of the plurality of PERE.
 5. Theapparatus of claim 1, wherein comparing the image signal at the firstdetection time to the image signal at the second detection timecomprises summing the squares of the differences between each of therespective image signals at the first detection time to thecorresponding image signals at the second detection time.
 6. Theapparatus of claim 1, wherein the optical imaging source comprises aone-dimensional laser source.
 7. The apparatus of claim 1, wherein theoperations further comprise receiving, via the spatially distributedplurality of photoelectric receiving elements (PERE), a distancemeasurement to the target object.
 8. The apparatus of claim 7, whereinthe operations further comprise generating the jam detection signal onlyif the received distance measurement to the target object is within apredetermined qualified range.
 9. The apparatus of claim 1, wherein avalue of the image signal is adjusted to zero if the image signal isless than a predetermined minimum signal threshold.
 10. The apparatus ofclaim 1, wherein the operation to determine a frame differential image(FDI) value comprises normalizing the FDI as a function of a number ofthe image signal values that are non-zero.
 11. The apparatus of claim 1,wherein each generated jam detection signal is a function of anintensity of the corresponding reflection of the linear optical beam offof the target object.
 12. The apparatus of claim 1, wherein each of aplurality of temporally spaced detection times comprises a correspondingtime interval during which each of the corresponding jam detectionsignals are generated.
 13. The apparatus of claim 1, wherein thespatially distributed plurality of photoelectric receiving elements(PERE) comprises a linear array of PERE.
 14. The apparatus of claim 1,wherein the spatially distributed plurality of photoelectric receivingelements (PERE) comprises a two-dimensional array of PERE.
 15. Theapparatus of claim 1, wherein the detection signal processing modulecomprises an analog-to-digital converter.
 16. The apparatus of claim 1,wherein the detection signal processing module and the processor furthercomprise a microcontroller.
 17. A monitor system for non-contact motiondetection comprising: a processor; an optical imaging source comprisinga spatially distributed plurality of photoelectric receiving elements(PERE) and configured by the processor to detect motion in a monitoredenvironment; and a data store operatively coupled to the processor andcontaining instructions that, when executed by the processor, cause theprocessor to perform operations comprising: comparing, for each of theplurality of PERE, values of the PERE processed by the optical imagingsource to a predetermined minimum value; determining, for each of thePERE, a frame differential image (FDI) value based on the comparisons;determining an amount of change based on an analysis of a differencebetween an FDI value at a first time and an FDI value at a second time;comparing the determined amount of change with a predeterminedthreshold; and generating a signal that indicates a jam state of themonitored environment when the comparison meets at least onepredetermined criterion.
 18. The monitor system of claim 17, furthercomprising an application specific integrated circuit (ASIC) comprising:an interface for connection to the processor, and circuitry forcontrolling operations of the processor.
 19. A method of non-contactmotion detection comprising: sampling of a target object by an opticalimaging source provided with a plurality of temporally separatedphotoelectric receiving elements (PERE) to generate correspondingtemporally separated pixel images; determining, for each of theplurality of PERE, a frame differential image (FDI) value indicative ofa measure of movement of a target object from a first detection time toa second detection time, the FDI value generated based on the temporallyseparated pixel images; comparing a first of the FDI values tocorresponding values of the FDI values of the temporally separated pixelimages; assessing whether or not the FDI values are less than apredetermined threshold value; and generating a jam state signalresponsive to one or more FDI values being less than the predeterminedthreshold value for a predetermined period of time.
 20. The method ofclaim 19, wherein comparing corresponding frame differential image (FDI)values comprises summing the square of a difference between the currentFDI value and a previous FDI value.